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Combinatorial screen of dynamic mechanical stimuli for predictive control of MSC mechano-responsiveness
Mechanobiological-based control of mesenchymal stromal cells (MSCs) to facilitate engineering and regeneration of load-bearing tissues requires systematic investigations of specific dynamic mechanical stimulation protocols. Using deformable membrane microdevice arrays paired with combinatorial exper...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8104874/ https://www.ncbi.nlm.nih.gov/pubmed/33962940 http://dx.doi.org/10.1126/sciadv.abe7204 |
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author | Liu, Haijiao Usprech, Jenna F. Parameshwar, Prabu Karthick Sun, Yu Simmons, Craig A. |
author_facet | Liu, Haijiao Usprech, Jenna F. Parameshwar, Prabu Karthick Sun, Yu Simmons, Craig A. |
author_sort | Liu, Haijiao |
collection | PubMed |
description | Mechanobiological-based control of mesenchymal stromal cells (MSCs) to facilitate engineering and regeneration of load-bearing tissues requires systematic investigations of specific dynamic mechanical stimulation protocols. Using deformable membrane microdevice arrays paired with combinatorial experimental design and modeling, we probed the individual and integrative effects of mechanical stimulation parameters (strain magnitude, rate at which strain is changed, and duty period) on myofibrogenesis and matrix production of MSCs in three-dimensional hydrogels. These functions were found to be dominantly influenced by a previously unidentified, higher-order interactive effect between strain magnitude and duty period. Empirical models based on our combinatorial cue-response data predicted an optimal loading regime in which strain magnitude and duty period were increased synchronously over time, which was validated to most effectively promote MSC matrix production. These findings inform the design of loading regimes for MSC-based engineered tissues and validate a broadly applicable approach to probe multifactorial regulating effects of mechanobiological cues. |
format | Online Article Text |
id | pubmed-8104874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-81048742021-05-17 Combinatorial screen of dynamic mechanical stimuli for predictive control of MSC mechano-responsiveness Liu, Haijiao Usprech, Jenna F. Parameshwar, Prabu Karthick Sun, Yu Simmons, Craig A. Sci Adv Research Articles Mechanobiological-based control of mesenchymal stromal cells (MSCs) to facilitate engineering and regeneration of load-bearing tissues requires systematic investigations of specific dynamic mechanical stimulation protocols. Using deformable membrane microdevice arrays paired with combinatorial experimental design and modeling, we probed the individual and integrative effects of mechanical stimulation parameters (strain magnitude, rate at which strain is changed, and duty period) on myofibrogenesis and matrix production of MSCs in three-dimensional hydrogels. These functions were found to be dominantly influenced by a previously unidentified, higher-order interactive effect between strain magnitude and duty period. Empirical models based on our combinatorial cue-response data predicted an optimal loading regime in which strain magnitude and duty period were increased synchronously over time, which was validated to most effectively promote MSC matrix production. These findings inform the design of loading regimes for MSC-based engineered tissues and validate a broadly applicable approach to probe multifactorial regulating effects of mechanobiological cues. American Association for the Advancement of Science 2021-05-07 /pmc/articles/PMC8104874/ /pubmed/33962940 http://dx.doi.org/10.1126/sciadv.abe7204 Text en Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Research Articles Liu, Haijiao Usprech, Jenna F. Parameshwar, Prabu Karthick Sun, Yu Simmons, Craig A. Combinatorial screen of dynamic mechanical stimuli for predictive control of MSC mechano-responsiveness |
title | Combinatorial screen of dynamic mechanical stimuli for predictive control of MSC mechano-responsiveness |
title_full | Combinatorial screen of dynamic mechanical stimuli for predictive control of MSC mechano-responsiveness |
title_fullStr | Combinatorial screen of dynamic mechanical stimuli for predictive control of MSC mechano-responsiveness |
title_full_unstemmed | Combinatorial screen of dynamic mechanical stimuli for predictive control of MSC mechano-responsiveness |
title_short | Combinatorial screen of dynamic mechanical stimuli for predictive control of MSC mechano-responsiveness |
title_sort | combinatorial screen of dynamic mechanical stimuli for predictive control of msc mechano-responsiveness |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8104874/ https://www.ncbi.nlm.nih.gov/pubmed/33962940 http://dx.doi.org/10.1126/sciadv.abe7204 |
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